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leozw/README.md

Leonardo Zwirtes

Head of Engineering

AI-Native Observability Architect · Full-Stack Engineer (Cloud → On-Prem) · OSS Builder · Extreme Executor

I design and build systems that observe, explain, and fix themselves — from the kernel-level instrumentation all the way up to the AI agents reasoning over the signals.

I work at the intersection of:

  • AI-native systems — agents, RAG, autonomous reasoning
  • Software & Systems Architecture — clean architecture, distributed systems at scale
  • Observability — the full LGTM stack, deep OpenTelemetry, zero-code instrumentation
  • Kubernetes & Cloud — cloud-native and bare-metal on-prem
  • Autonomous Root Cause Analysis — incidents that explain themselves

🚀 What I Do

I'm a real full-stack engineer — backend, infra, AI, and the glue in between — and I lead engineering at Elven Works. I build production-grade systems with obsessive attention to reliability, performance, and clarity.

  • Architect and lead AI-powered observability platforms end to end
  • Build zero-code instrumentation layers for Lambda, Node.js, .NET, Python, and React Native
  • Design autonomous root cause analysis systems backed by knowledge graphs
  • Engineer distributed microservices at scale (Go + Python, clean architecture)
  • Create OSS tooling around OpenTelemetry, logs, traces, and metrics
  • Run Kubernetes from managed cloud (EKS/AKS) down to on-prem (RKE2, bare metal)
  • Turn chaos into structured, actionable signals

🧠 Core Focus Areas

  • AI for Observability & Autonomous Root Cause Analysis
  • OpenTelemetry deep instrumentation (eBPF, tail sampling, cardinality control)
  • Kubernetes — cloud-native and on-prem
  • LGTM Stack (Loki, Grafana, Tempo, Mimir) + OpenObserve
  • AI-native backend systems (multi-agent orchestration, Temporal workflows)
  • High-performance, zero-code Lambda instrumentation
  • Vector search & embeddings (Qdrant, RAG, MiniLM)
  • Knowledge graphs for systems reasoning (Neo4j)
  • Infrastructure as Code & platform engineering

🛠 Tech Stack

Languages Go · Python · TypeScript · Node.js · Lua

AI / ML LLMs · RAG · Vector DBs · Qdrant · vLLM · Temporal · Multi-Agent Systems

Observability OpenTelemetry · Grafana · Loki · Tempo · Mimir · OpenObserve · Beyla / eBPF · Zabbix · k6

Cloud & Infra AWS · EKS · AKS · Kubernetes · RKE2 · On-Prem / Bare Metal · Terraform · Kong · Keycloak · NATS · Cloudflare

Data Neo4j · MongoDB · Redis · Kafka


🏗 Major Projects

  • Elven Observability — AI-powered, LGTM-based observability SaaS (Datadog-quality, OSS core)
  • Sentinel — AIOps platform: microservices fleet, AI agents, RAG, Temporal workflows, time-series ML
  • Autonomous RCA Engine — hypothesis-driven incident investigation over Neo4j evidence graphs
  • Elven Connect — secure reverse-tunnel datasource connectivity (gRPC / mTLS)
  • Kyrvex — secrets management platform
  • Zero-Code Telemetry — multi-language log/trace collectors (Go, .NET, JS, Python, React Native)
  • Kubernetes Copilot — AI-assisted cluster interaction

🧩 What Makes Me Different

  • Extreme focus — I go deep, full-stack, top to bottom.
  • I don't fear complexity — I instrument it.
  • I build what I wish existed, then ship it.
  • I solve the problems most people avoid.
  • I lead by building alongside the team, not just above it.

🌍 Mission

To make systems explain themselves. To build AI-native infrastructure that reduces operational anxiety. To turn observability into intelligence.


📈 Currently Building

  • AI-native observability platform with autonomous SRE assistants
  • Observability + Security convergence
  • Zero-code telemetry for everything
  • Knowledge-graph-driven reasoning over live systems

⚡ Personal

I'm married, I have two kids, two cats, and so many plants that I basically run Kubernetes at home too — just with less documentation and more crying.


"Complexity is inevitable. Confusion is optional."

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